Research methods and advanced data analysis in public health


Subject carrier


• Systematic literature review with meta-analysis (PRISMA, meta-analysis, tools to support systematic literature review and meta-analysis, reporting systematic literature review and meta-analysis findings)

• Research methods in public health
o Methodological peculiarities of research in public health
o Quantitative and qualitative approach to research
o Triangulation principle and combination of quantitative and qualitative methods approaches
o Sampling in quantitative and qualitative studies and conclusions based on research results (sample size, statistical power, saturation principle)
o Tools for quantitative and qualitative research

• Validity and reliability of research instruments
o Questionnaire development/adaptation/ translation procedure
o Assessment of the validity and reliability of measuring instruments
o Validity and reliability in qualitative research methods

• Programming basics for data processing and analysis
o Programming principles (syntax, conditional/embedded statements, etc.)
o Basic commands for data processing
o Data transformation
o Practical programming in a selected program environment (e.g. Mathlab)

• Advanced statistical methods
o General Linear Model (GLM)
o Multivariate GLM
o Multiple linear and binary logistic regression
o Advanced forms of correlations
o Discriminant analysis
o Factor analysis (factor analysis types and their use)

• Data mining and decision models
o Data mining methods
o Data preparation
o Data visualization
o Decision models basics
o Data mining and decision models tools

• Structural modelling (SEM) and path analysis
o Conditions for implementing SEM
o Quality of the model
o Tools for SEM